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--- |
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license: mit |
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base_model: microsoft/deberta-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: deberta-base-clickbait-task1-20-epoch-post_title |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# deberta-base-clickbait-task1-20-epoch-post_title |
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This model is a fine-tuned version of [microsoft/deberta-base](https://huggingface.co./microsoft/deberta-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.5412 |
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- Accuracy: 0.7025 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| No log | 1.0 | 200 | 0.7414 | 0.7075 | |
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| No log | 2.0 | 400 | 0.6972 | 0.73 | |
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| 0.7437 | 3.0 | 600 | 0.7188 | 0.73 | |
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| 0.7437 | 4.0 | 800 | 0.9260 | 0.7225 | |
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| 0.3148 | 5.0 | 1000 | 1.0694 | 0.715 | |
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| 0.3148 | 6.0 | 1200 | 1.3980 | 0.735 | |
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| 0.3148 | 7.0 | 1400 | 1.6897 | 0.7125 | |
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| 0.103 | 8.0 | 1600 | 1.8628 | 0.7275 | |
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| 0.103 | 9.0 | 1800 | 2.0991 | 0.7125 | |
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| 0.0456 | 10.0 | 2000 | 2.0466 | 0.7225 | |
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| 0.0456 | 11.0 | 2200 | 2.2220 | 0.7225 | |
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| 0.0456 | 12.0 | 2400 | 2.3278 | 0.6975 | |
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| 0.0222 | 13.0 | 2600 | 2.4275 | 0.7025 | |
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| 0.0222 | 14.0 | 2800 | 2.4249 | 0.695 | |
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| 0.0092 | 15.0 | 3000 | 2.4740 | 0.7275 | |
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| 0.0092 | 16.0 | 3200 | 2.4897 | 0.7125 | |
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| 0.0092 | 17.0 | 3400 | 2.5280 | 0.705 | |
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| 0.0058 | 18.0 | 3600 | 2.5360 | 0.705 | |
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| 0.0058 | 19.0 | 3800 | 2.5075 | 0.715 | |
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| 0.0039 | 20.0 | 4000 | 2.5412 | 0.7025 | |
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### Framework versions |
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- Transformers 4.44.0.dev0 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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